Blind source separation (BSS), also known as blind signal separation, is the separation of a set of source signals from a set of mixed signals.
Instantaneous, single-channel blind source separation (BSS) deals with the problem of obtaining M estimates ŝi(n), i=1, . . . , M of the M source signals si(n) if only a linear mixture x(n)=Σi=1Msi(n) of them is given.
One application for BSS is the separation of music into the individual instrument tracks such that an upmixing of the original content is possible.
A known approach to Single-channel BSS is Single-channel BSS using non-negative matrix factorization (NMF). Single-channel BSS using non-negative matrix factorization usually consists of transforming the mixture x(n) into the time-frequency domain using a short-time Fourier transform (STFT), applying NMF to its magnitude spectrum in order to obtain frequency basis vectors and corresponding activation vectors which are summarized in a frequency matrix W and an activation matrix H and, finally, using a suitable clustering such that the components are grouped into clusters.